Identifying a cohort of hospitalized chronic kidney disease patients using electronic health records: lessons learnt and implications for future research and clinical practice guidelines

Background. Safe medication prescribing for hospitalized chronic kidney disease (CKD) patients is challenging. Leveraging electronic health records (EHRs) offers potential for decision support. A first step is to capture the CKD cohort through so called electronic phenotypes (e-phenotypes). However, available e-phenotypes, defined by logical rules applied to EHR data, lack consensus and are often inconsistently aligned with the Kidney Disease – Improving Global Outcomes (KDIGO) guideline for CKD (KDIGO-CKD). Therefore, local analyses and formalization efforts are essential to derive logical rules for CKD cohort selection. Methods. We analyzed routinely collected EHR data from adults hospitalized at Amsterdam University Medical Centre (2018–23). Six logical rules were investigated: four derived from KDIGO-CKD (reduced glomerular filtration rate, albuminuria, kidney replacement therapy, and other markers of kidney damage) and two from published studies (diagnosis codes and medications). Results. The study included 108 854 hospitalized patients. Extensive efforts were needed to formalize the clinical CKD definition from KDIGO-CKD and adapt it to EHR data, including selecting appropriate CKD diagnosis codes, medications, and computable criteria. Pooling six logical rules resulted in identifying 17 805 hospitalized CKD patients (16.4%), showcasing varying CKD patient counts per rule (with proportions ranging from 2.1% to 8.4%). Nonetheless, baseline characteristics across cohorts were comparable. Over one-third of patients identified by decreased eGFR or albuminuria/proteinuria measurements lacked a corresponding diagnosis code. Conclusions. Deriving and formalizing six logical rules required close collaboration between nephrologists, EHR data experts, and medical informaticians. Our study provides groundwork towards a computer-interpretable CKD definition to standardize cohort capture in EHR-based studies.